As a new interdisciplinary field, computer vision has made great progress in both theoretical research and practical application. Especially, following the development of image processing technology and computers with high performance in recent years, computer vision has been applied in many practical applications, such as target identification, surveying and mapping, industrial measurement, industrial control, automatic navigation and military application, etc.
The simulation of camera imaging can provide a convenient and quick experiment platform for the study of computer vision to get simulation data under various conditions, which saves money and shortens the time for study. Therefore, it is significant in the process of the study of the computer vision. Especially, when the actual operating conditions are special, the simulation system becomes more important, such as aerial mapping which is to get realtime 3D terrain data but where a computer vision algorithm cannot be carried under the actual flight environments based on cost or time constraints.
At present, the simulations of computer vision are almost digital simulations. Although complete software simulations could reduce the cost and time of study and experimentation to a minimum level, it is difficult to establish mathematical models for complex computer vision systems. The complex systems have to be simplified for complete software simulations, so disparities exist between the conditions of the complete digital simulation and the actual working condition because of excessive idealization. Especially when the camera exhibits lens distortion and stronger noises interfere, the truthfulness and reliability of images acquired by complete digital simulation become bad. Hardware-in-the-loop simulations can overcome above insufficiency. Hardware-in-the-loop simulation systems replace the mathematical model of the performance hardware with the hardware itself in order to approach the actual condition for a more accurate simulation result. These hardware-in-the-loop systems are economical means of computer vision study and experiment under various conditions, such as the utilization to testify the correctness and evaluate the performance of computer vision algorithm in the initial stage of study.
The hardware-in-the-loop simulation system has to integrate software with hardware. It is rather difficult to establish the system model between software and hardware to determine the relationship between the virtual reality scene and the real-life camera image, so it is a bottleneck of computer vision hardware-in-the-loop simulation. There is no hardware-in-the-loop simulation system or method to solve the above problem for computer vision mentioned in the existing literatures at present. So it is necessary and urgent to solve the bottleneck problem and set up a practical and efficient hardware-in-the-loop simulation system for computer vision.